Thursday, January 19, 2017

Stop Listening, Start Watching. How Interest-Based Segmentation Gets to the Heart of Consumers

By: Hannah Chapple

In recent years, we've seen companies increase their reliance on social data. Why? Today there are more social signals than ever. Consumers are sharing comments, their interests, thoughts, and more online. The result being an incredible amount of consumer-provided data at our fingertips.

The problem facing marketers is trying to make sense of the deep end of social data. One way we’ve seen businesses and big brands try to make sense of this data is by investing in a little something called social listening. If we watch and listen to what consumers are saying in real-time, we'll paint a more accurate picture of them, right? Wrong.

Social listening is biased. Many times our online persona is different than who we are or doesn't show us in our entirety. And only a small percentage of those online ever actually engage or vocalize their thoughts, interests, and beliefs – the consumer insights that companies crave.

I'll use myself as an example. If you comb through my social feeds (and please, don't feel you have to) you'll find my comments and a flurry of articles shared on all things marketing. While I am interested in this stuff, yes (it's my profession after all), it is not the complete picture of who Hannah is as a person.

So how do we get to the heart of the consumer?

One way companies can figure out who their consumers are and what they want is by leveraging interest-based segmentation.

Interest-based segmentation is when individuals are clustered and segmented into naturally-occurring, unbiased clusters, by looking at who or what they choose to follow. Instead of focusing on the vocal minority, at Affinio we consider following patterns and interest data to be paramount to listening or traditional research methods. 

 Image: Interest-based clusters generated by Affinio

Following and connecting with other people is a fundamental property of social behaviour. It is also a silent action, whereas social biases might keep individuals from being honest about their interests (who they follow) or what they talk about in person. The takeaway: you wouldn't know everything that I'm interested in just by looking at what I say, but you would understand my interests by looking at who I follow.

By focusing on how an audience is connected (analyzing their shared interests and affinities), interest-based segmentation gets to the very heart of the consumer. Instantly, companies can identify who and what their audience cares about, even if they've never vocalized it. Or if they have, this method validates that finding. This approach places focus on the honest relationships consumers have built and maintained and lets marketers understand their audience as human beings and not one-dimensional data points.

About the Author: Hannah Chapple is the Marketing & Content Coordinator at Affinio, the marketing intelligence platform. Hannah holds a Bachelor of Business Administration with a major in Marketing from the F.C. Manning School of Business at Acadia University. 

Wednesday, January 18, 2017

See Who You’ll Meet at The Media Insights & Engagement Conference

See Who You’ll Meet at The Media Insights & Engagement Conference

The Media Insights & Engagement Conference WILL Sell Out…

Don’t worry, there’s no need to panic yet!

There’s still time for you to secure your spot at your industry’s annual meeting place AND save $100:

Still not convinced that you need to be at The Media Insights & Engagement Conference? Your competitors have already signed up – don’t get left behind as they uncover what’s next for the industry and how to stay ahead.

20th Television
21st Century Narrative
A&E Networks
AMC Networks
Annik Inc
BBC America
BET Networks
Bravo and Oxygen Media
Charter Communications
Cint USA Inc
Clarion Research Inc
Chadwick Martin Bailey
Consensus Point
Cooper Smith Advertising
Council for Research Excellence
Country Music Association
Creative Artists Agency
Discovery Communications
Disney ABC Television Group
Disney Channel Worldwide and Freeform
Disney World
Dreyfus Advisors LLC
Frank N Magid Associates
Fuel Cycle by Passenger
Fuse Media
Fusion Media Group
HBO Latin America
Horowitz Research
Hub Entertainment Research
Insight Strategy Group
Invoke Solutions
Ipsos Connect
Katz Media Group
Leflein Associates
Lieberman Research Worldwide
Millward Brown
Miner & Co Studio
National Geographic Partners
NBC News
NBCUniversal Telemundo Enterprises
NC Solutions
Norman Hecht Research
Oakland A's
Phoenix Marketing International
Radius Global Market Research
RAG Media
RLS Media Consulting LLC
RSG Media
Screenvision Media
Scripps Network
Showtime Networks
Simmons Research
Sony Pictures Television
Spectrum Reach
Starz Entertainment LLC
Trend Hunter
TRP Research
Turner Broadcasting
Universal Music Group
University of Chicago
Vision Critical
Warner Brothers

Join YOUR industry at The Media Insights & Engagement Conference later this month – Use exclusive Blog discount code MEDIA17BL for an additional $100 off:

We hope to see you in Fort Lauderdale!

The Media Insights & Engagement Conference Team

Tuesday, January 17, 2017

Selling on Emotion: Why Show Ratings and Demographics No Longer Tell the Whole Story

By Jared Feldman, Founder & CEO of Canvs

An earlier version of this article appeared in AdAge.

With upfront season just around the corner, early signs are that brands, finally, are again buying more of what networks are selling.

That's great news for the networks, after over three straight years of declines in upfront ad-time purchases (and two years of plateaued spending before that). But as the buying season kicks off, let me suggest that brands should pay attention to some new factors this year as they lock in deals.

In the past, in making decisions about where to spend their ad dollars, buyers had only ratings and some demographic data about existing shows, plus a first peek at new ones coming in the fall. What I'd like to propose is that buyers not use, or just use, those same old methods this time around.

Oh sure, keep the ratings and demos you're used to working with. Nielsen's work continues to have value and it's evolving to embrace the new TV realities.

But show ratings and audience demographics by themselves no longer tell ad buyers everything they need to know in the new universe of "TV" we now live in. The TV audience is shifting, and in lots of directions at once. With it, the business is shifting, too.

Audiences are watching TV in more ways and on more platforms than ever, and at different times and in different settings. Just as importantly, audiences are talking about the shows they're watching, on more social media and chat and other online platforms than ever.

And when fans are talking about these shows, sharing important moments, creating content about the shows, and reacting to that, they're also evoking and expressing a whole raft of feelings and attachments about favorite programs.

The savviest programmers realize this. They're building shows that connect with and captivate dedicated, niche audiences who care deeply about that show. They're sharing compelling behind-the-scenes content, live tweeting with fans, and creating other experiences that will hook and engage the superfans who care most about a program.

And those shows and networks are exactly where advertisers should be. Those fans will be a show's best ambassadors. And the research says they'll also be the best ambassadors for brands advertising around that show.

The shows that stir emotional reactions are the ones that also will stir reactions and buying impulses for the ads of those shows. As they say in the business, that is gold. So it's important to figure out which companies are doing a good job reaching and holding those audiences your brand cares about most.

For instance, the two networks whose shows most often evoke the emotion "addicting" on Twitter were MTV and Freeform (then known as ABC Family), according to a Canvs analysis of tweets captured by Nielsen.

It shouldn't be a complete surprise -- both networks target millennials, who are tech-savvy and sharing-mad. They share everything they care about, including some of their favorite shows on those two networks.

"Addictive" programming isn't the only thing buyers should look for. For instance, what networks and shows do fans find consistently "funny?" A laughing fan is one predisposed to like the brands connected to those shows.

And though the industry may not be quite ready for it, let me propose another thing. Networks and show runners will become increasingly skilled at creating compelling niche programming for ardent superfan audiences. They're also going to get better at using the new measures of success and building to it.

At some point, as creators improve, and as brands integrate what this means for their bottom line, we'll have new network milestones for ad sales. Expect networks to begin guaranteeing more than just ratings.

Providing a minimum level of emotional reactions that can help drive advertising success will become important. And when a show doesn't drive that emotional response, a network will have to figure out how to make good on its promise.

By that point, the entire industry will know how much emotion matters in making a show, and its advertising, succeed. And then we'll really see the full power and value of advertising in the new TV universe.

Related articles

Thursday, January 12, 2017

How Are You Treating Your Organizational Data?

By: Anil Damodaran, Blueocean Market Intelligence Assistant Vice President

Data fragmentation has existed for over 15 years and still does today. However, the challenge has grown tremendously due to an increase in the number of data sources and devices in use, at the workplace and home. Today, data is generated and stored not only on office PCs and laptops, but on mobile devices such as smartphones, tablets, online storage devices, and more.

Most of this data is generated in bits and pieces during various activities like exchange of emails, feedbacks, chats, IoT feed captures, and pilot surveys. It lies around in devices or unused drives, and often treated as office stationery, until one day someone suddenly realizes the cost implications of this recklessness. According to research from Salesforce, about 53 percent of organizational data is left unanalyzed that could otherwise have signified an opportunity for decision makers.[1] The problem, at a grass-roots level, is leaving data unattended with disparate sources and not implementing proper data governance.

So what can we do?

Data fragmentation can be addressed if you start considering data generated within your organization as a corporate asset. By doing so, it will become more instinctive to institute practices and processes of measuring data. Once you can measure their data, it becomes easier to tag the data based on business relevance and quality attributes.

For example, in almost all companies large and small, it is common to take stock of infrastructure – tangible and intangible – and tag them, such as company IP, laptops, mouse, and so on to the employee using it. Similarly, are you then tagging your data generated within your organization to its source, purpose, time, format and so on? It has been found that only 13 percent organizations have properly integrated data and predictive insights extensively into their entire business operations.[2] Companies that drive their businesses using data-driven strategies are five percent more productive and realize six percent higher profits.[3]

Here are some of the traits of an organization that treat data as an asset vs. those that do not.[4]

Organization that treats data as an asset
Organization that does not treat data as an asset
Is more innovative
Less innovative and tends to become commoditized in the long run
Is more customer-centric
Pushes products to customers, instead of developing products based on customer needs
Harbors a culture of openness and collaboration
Politics and hierarchy based system tend to keep data in silos
Business decisions are data-driven
Run on personal experience and intuitions
Business processes and performance are measured based on feedback and analytical models
Practices age-old business processes; no system for measuring business performance
Risk mitigation is proactive
Risk mitigation is reactive

What kind of an organization are you and what is your biggest challenge with the evolution? Share with us your experience and views.

Blueocean Market Intelligence is a global analytics and insights provider that helps corporations realize a 360-degree view of their customers through data integration and a multi-disciplinary approach that enables sound, data-driven business decision. To learn more, visit

Monday, January 9, 2017

3 Ways Market Researchers Approach Mobile

By: Roddy Knowles, Director, Product & Research Methodology, Research Now 

 This post was originally published on Research Now’s Blog.

I’ve been saying (sometimes complaining or screaming) for years that as an industry we need to wake up and approach research with mobile in mind. I haven’t been alone here.

Several of my colleagues – here at Research Now and elsewhere – have pushed hard for change. Reminders for why we need to change are everywhere, whether that be in the statistic du jour about mobile usage, a dataset with more mobile participants than expected, or just sitting on a park bench watching throngs of people of all ages hunt for Pok√©mon.

In spite of constant everyday reminders and the call from many in the market research field, true change has been slow coming. So, how have market researchers kept pace with broader mobile trends and embraced a mobile-first philosophy?

I’ve conducted an incredibly unscientific segmentation of researchers – cute segment names and all – that attempts to capture what we’re all seeing if we look around at our colleagues.

Response 1 – Meet Bill

Response 2 – Meet Evan Tually
Response 3 – Meet Reese Istant

There is a bit of humor, a bit of shame, and a bit of truth in these characterizations. If you are in this industry I know you know people who look a bit like all 3 of these hypothetical folks. And I know you can call out your friends and colleagues for being a Reese Istant, or just ask them to be a bit more like Bill.

The simple truth in this silliness is that we know that embracing a mobile-first mindset is the best course forward, even if we do a good job suppressing this truth. I know that change is hard. We all know that change is hard. But the sooner we get there, the less painful it will be. And the good news is, we are not too late. Someday, we will have a room full of Bills and I’ll stop my poor attempts at market research humor.

Thursday, January 5, 2017

Marketing Analytics and Data Science 2017 - Save the Date

Save The Date!
April 3-5, 2017, San Francisco, CA

The U.S. election results proved that there is an urgent need to improve our prediction models and statistical analysis. Thankfully, Data science and Advanced Analytics are starting to lead the charge, and that’s a fundamental reason it’s being called the sexiest job of the 21st century.

The Marketing Analytics and Data Science conference is your opportunity to go beyond the data and identify hidden insights. How can you work together to filter through all the clutter of data and deliver results that really make a difference?

You are more powerful together than you are on your own!

Join Superheros from:

·         Director, Alibaba Group
·         Chief Data Scientist, Mashable
·         Founder and CEO, Fast Forward Labs
·         Head of Customer Experience Analytics and Experimentation, Paypal
·         Economic Research Scientist, Netflix
·         EVP Insight, BBC Worldwide
·         Chief Economist, Google
·         Visiting Executive, Harvard Business School
·         And more!

Use exclusive LinkedIn discount code MADS17BL and save $100! Buy your tickets here:

We hope to see you in San Francisco next spring!

The Marketing Analytics & Data Science Team

Wednesday, January 4, 2017

The Future of Market Research Data Collection

By: Research Now CEO Gary S. Laben

This post was originally published on the Research Now Blog.

The vast expansion of communications technology has obviously sparked a dramatic change in the way our world functions. Certainly one of the most ubiquitous and transformational impacts is that brought on by new technologies that allow virtually everyone to remain constantly and instantly connected; connected to one another, certainly, but also to the growing number of systems upon which we are growing increasingly dependent, if not addicted. Modern communications systems have given users unprecedented access to information and services without regard to time or location, letting them get more done faster than ever before. Even more, the devices and systems continually monitor users’ behaviors to refine the responses to personalize the service delivered. By providing experiences that are tailored and relevant to each user’s expectations, this new generation of technology doesn’t just provide a better user experience, it also preserves the user’s most valuable resource: time.

The idea that we can use deep knowledge about individual and groups of users’ situations, preferences, and past behavior to provide a better, more efficient user experience applies equally well to market research. Of course, this is not a new idea. We’ve always used profiling data to target specific communities for research studies and minimize the amount of information we need to collect in each study. Avoiding collecting redundant data shortens surveys, reduces participant load, and improves data quality. What’s changing is the vast volume of data we can mine to automatically extract and maintain components of the user’s profile – even in real time – without the need to explicitly query them. This is the realm of big data.

Applying big data to market research has tremendous benefits to all involved in the research process. Data providers can use automation to maintain more expansive and accurate research databases at a lower cost. Market researchers can target research communities with greater accuracy and know more about them in advance of fielding a study, which lets them devote more of a survey to the core questions of the research rather than qualifying questions. And finally, and perhaps most importantly, the study participants benefit from reducing the number of tedious and repetitive profiling questions asked of them, shortening surveys, keeping them engaged, and giving them back valuable time.

The allure and promise of big data for market research is compelling, but not without risks and issues. Technology has created a window of opportunity for brands to know more about consumers than previously ever thought to be possible. But, just because we can reach everybody, doesn’t mean we should. Technology sometimes presents a facade that can lead researchers to lose sight of the fact that they are dealing with real people. Real people who have thoughts, feelings, emotions, goals, dreams, and likes and dislikes. Dehumanizing a person to a set of numbers and patterns obscures the advantages that big data enables. Further, easy collection of data can make us forget about the very real and important privacy interests of our participants. If we fail to recognize, respect, and account for these concerns, we will lose their trust and their willingness to participate.

The market research industry must use big data as an opportunity to get smarter, quicker, so that we are able to be more personable in our approach to collecting information. We need to maximize participants’ time by creating relevant engagement for them that is also useful to the researchers. Big data presents a new opportunity to improve our ability to accomplish both.
At Research Now, having more data, specifically more accurate data, about people is what defines the quality of our panels. It allows us to be less intrusive and more in-the-moment with people who want to engage with brands. Having more information about whom we’re talking to permits us to put greater focus on core research by bypassing things like screeners and get right down to the questions our clients are interested in asking.

This improves the participant experience and gives our research clients the ability to collect more desirable data, which in turn fuels deeper insights and gives everyone back just a little more of their precious time.

Tuesday, January 3, 2017

How Millennials Are Changing Their Relationship to Retail

This post was originally published on Kelton Global’s blog.

Consumers of Generation X age and older grew up as relatively passive shoppers, able to do little more than recommend a product to a handful of friends, vent to a salesperson or write a letter to corporate headquarters. But Millennials have a very different relationship with brands and companies.

As mass-consumption natives, they see themselves as collaborators and co-marketers instead of ‘the audience’ or ‘the target.’ They’re ready to champion their favorite brands online – and equally willing to criticize those with subpar products or ethics. Digitally savvy and highly entrepreneurial, the Millennial generation departs from the larger consumer base in a few key ways:

They want you to reflect their values.

According to a recent Pew Research study, fifty-five percent of Millennials’ believe churches and other religious organizations have a positive impact in the U.S. (Seventy-three percent thought so in 2010). Indeed, more than one third of Millennials are not affiliated with any faith. So they look to brands instead to represent their values, with around 81 percent of them expecting brands to be responsible global citizens.  A 2016 Deloitte Millennial Survey revealed that 87 percent of this demographic don’t consider a company successful on financial merit alone, but want evidence of corporate social responsibility as well.

Millennials are loyal supporters of companies with strong reputations for CSR. Toms, which sells shoes, sunglasses and apparel, has been a hit because of its wide-reaching commitment to charitable causes via the One to One CampaignCuyana, which sells high quality women’s basics and promotes a simpler lifestyle, is also popular with Millennials. Through its “Lean Closet” initiative, Cuyana offers consumers the chance to donate clothes to women in need. Customers are offered a $10 credit towards their next purchase for every donation they make.

They crave simplicity.

According to Accenture, spending by Millennials will grow to $1.4 trillion annually by 2020. But their spending mentality is selective; they have access to a vast range of goods but are highly conscious of the impact of their consumption. The mindset has shifted from ‘one of everything’ to ‘only the essentials’ – and they want to know where those essentials were made, by whom and with what materials.

They have higher expectations for customized, seamless service.

Just as there has been a shift from material to experiential spending across generations, the experiential part of the shopping experience has become increasingly important for Millennials. Mens clothing retailer Bonobos, which offers a personalized shopping experience in a showroom setting, has struck a chord with a younger crowd turned off by the generic, impersonal process of shopping at traditional brick and mortar retailers like the Gap.

They expect you to listen. And activate, quickly.

Millennials love to challenge brands– and they know how to do it well. They’ll keep up the pressure on a company until it amends a problem in a tangible and authentic way. And if they’re frustrated by the slow pace of change, they won’t hesitate to disrupt the status quo and start their own company. Having grown up in the era of Shark Tank & Facebook millionaires, they are natural entrepreneurs with the information, tools and confidence to do so.

The attitude of the hip new health insurance company Oscar, which aims to be transparent and unbureaucratic, sums up Millennial attitudes perfectly. Its website states: “We wanted a better healthcare company. So we built one.”

Brands take note: Millennials don’t want a story dictated to them – they want to be part of an evolving, authentic narrative that goes beyond simple marketing and branding.

Thursday, December 29, 2016

Our New Year’s Resolution: Focusing on Your Future

We want you to continue to be successful in 2017. In order to do that, when it comes to business, you need to think about the future beyond next year.  

We know you are under pressure from your managers to stay ahead of the curve and always be thinking of the future in your industries. So, that’s why it’s more important than ever to attend live conferences and events to hear what the future holds directly from industry leaders.

Here are the events that will keep you thinking ahead in 2017:

·         The Media Insights & Engagement Conference
January 31 - February 2, 2017
The Ritz-Carlton, Fort Lauderdale, FL
Use code MEDIA17BL for an additional $100 off
Learn more and buy tickets:

·         Marketing Analytics & Data Science
April 3 – 5, 2017
JW Marriott San Francisco Union Square, San Francisco, CA
Use code MADS17BL for an additional $100 off
Learn more and buy tickets:

·         FUSE Miami
April 4-6, 2017
Nobu Hotel – Eden Roc, Miami, FL
Use code FUSE17BL for an additional $100 off
Learn more and buy tickets:

·         FEI: Front End of Innovation
May 8-11, 2017
Seaport World Trade Center Boston, MA
Use code FEI17BL for an additional $100 off
Learn more and buy tickets:

·         OmniShopper
June 20-22, 2017
Hyatt, Minneapolis, MN
Use code SHOPPER17BL for an additional $100 off
Learn more and buy tickets:

·         TMRE: The Market Research Event
October 23-25, 2017
Rosen Shingle Creek, Orlando, FL
Use code TMRE17BL for an additional $100 off
Learn more and buy tickets:

·         TMRE Digital
With TMRE Digital you can access 27 Sessions from the World's Leading Insights Event TMRE from the comfort of your own home or office.
Learn more and download:

Don’t get stuck in the past. Look forward to the future!  

We hope to see you at our 2017 events!


The Knect365 Team

Friday, December 16, 2016

Image Recognition and the Future of Digital Analytics

This post was originally published on the Kelton Global Blog.

The days of text-centric social feeds are officially long gone. A whopping 1.8 billion images are uploaded to the Internet daily and of those, 350 million are shared on Facebook. Instagram recently surpassed 500 million active users, and Snapchat now has more active users than Twitter. The content that flows into our social feeds is more heavily optimized than ever to deliver more of what people want—less text and more visuals.

Brands have adapted their social content strategies accordingly by delivering more visually immersive experiences. And while we’re seeing significant shifts in branded content, this influx of visual content has yet to herald a commensurate change in social analytics. Accordingly, few gains have been made to measure and derive insights from the contents of images or video. Social listening has historically focused on the challenges of text-based analysis–specifically, the challenge of determining the context and meaning behind posts. But as social media habits evolve, it’s clear that deriving insights from pictures is an increasingly important aspect of understanding consumers. That’s where image recognition comes into play.

Brands have adapted their social content strategies accordingly by delivering more visually immersive experiences.

Simply put, image recognition is the process of translating images to data. Photos and images can reveal a wealth of data points–demographics, purchases, personalities, and behaviors (just to name a few). Through next generation image recognition, a mere selfie may reveal a person’s gender, approximate age, location disposition, and even the clothing brands that the person is wearing. As text-centric media takes a backseat to image and video, the opportunity to understand the contents of these formats grows. These insights represent a veritable treasure trove of actionable data for brands.
Tools that analyze image and video-based content are still in development, but increased investment in research is already impacting commercial products and how they’re advertised. One example is brand logo recognition–scanning images for brand logos, and flagging them with the corresponding brand names. This tool is especially powerful considering that 80% of photos shared online depict a brand logo but don’t explicitly call out the brand’s name. This fact points to a sizable opportunity for companies to measure and understand the impact of these formerly inaccessible data points.

Photos and images can reveal a wealth of data points–demographics, purchases, personalities, and behaviors (just to name a few).

As an example of how this applies to brands, Kelton’s Digital Analytics team took a look at the scores of backyard BBQ photos that flooded public forums, blogs, and social feeds over the recent 4th of July holiday. We experimented to see which of two quintessentially American beverage brands–Coca-Cola and Budweiser–netted more published images of patriotically-themed bottles and cans (as well as other forms of branding) on social media.

In the end, Coca-Cola branding was twice as prominent as Budweiser’s. We found that Coke bottles and cans popped up in more diverse settings such as public parks and inside motor vehicles, whereas Budweiser was predominantly found in bars and house parties. Coke also aroused greater sentiment around the theme of Americana, as many consumers photographed vintage Coca-Cola gear and opted for bottles over cans. This might explain why Coke captured a significantly greater share of social mentions than Budweiser.
This example illustrates several ways that brands can leverage image recognition technology to build actionable insights:

·         Ethnographic data – Identify where, when and how often brands are showing up in people’s lives.
·         Updated brand health analysis – We now have a more comprehensive point of view of brands’ online footprint.
·         Sponsorship and Branding ROI – Extend the value of branding and sponsorships shared via online news, blogs and social media through a multiplier effect.
·         Influencer identification – Find authentic brand advocates who consume and spotlight your merchandise.
·         Misuse use of brand iconography – Surface content that depicts improper usage of brand’s logo or other creative assets.

In today’s ever-shifting social media landscape, it’s never been more important for brands and their partners to stay aware of the new and emerging capabilities that can help better understand consumers’ behavior online. Image recognition is just the beginning. From AI startups to instant objection recognition devices, the mobilization and fusion of research, tech, and capital is quickly reshaping the way we think about analytics. These new tools will add even more contextual understanding to sentiment on social platforms, empowering brands to understand consumers like never before.